Industrial Demand-Side Management by Means of Differential Evolution Considering Energy Price and Labour Cost

Alessandro Niccolai (), Gaia Gianna Taje, Davide Mosca, Fabrizio Trombello and Emanuele Ogliari
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Alessandro Niccolai: Department of Energy, Politecnico di Milano, 20133 Milan, Italy
Gaia Gianna Taje: Department of Energy, Politecnico di Milano, 20133 Milan, Italy
Davide Mosca: Ratti S.p.a. Società Benefit, 22070 Guanzate, Italy
Fabrizio Trombello: Ratti S.p.a. Società Benefit, 22070 Guanzate, Italy
Emanuele Ogliari: Department of Energy, Politecnico di Milano, 20133 Milan, Italy

Mathematics, 2022, vol. 10, issue 19, 1-16

Abstract: In the context of the high dependency on fossil fuels, the strong efforts aiming to shift towards a more sustainable world are having significant economic and political impacts. The electricity market is now encouraging prosumers to consume their own production, and thus reduce grid exchanges. Self-consumption can be increased using storage systems or rescheduling the loads. This effort involves not only residential prosumers but also industrial ones. The rescheduling process is an optimisation problem that can be effectively solved with evolutionary algorithms (EAs). In this paper, a specific procedure for bridging demand-side management from the theoretical application to a practical industrial scenario was introduced. In particular, the toroidal correction was used in the differential evolution with the aim of preventing the local minima worsening the effectiveness of the proposed method. Moreover, to achieve reasonable solutions, two different cost contributions have been considered: the energy cost and the labour cost. The method was tested on real data from a historical textile factory, Ratti S.p.A. Due to the nature of the loads, the design variables were the starting time of the 30 shiftable loads. The application of this procedure achieves a reduction in the total cost of approximately 99,500 EUR/year.

Keywords: demand side management; prosumers; evolutionary optimisation; load shifting (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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